1. Field of the Invention
This invention relates to a computerized, networked complex using an expert or rule-based or other artificially intelligent system (e.g., artificial neural network, genetic algorithm, etc.) to help teams or groups become more effective by improving communications between members of the team. The system employs skills generally known to and used by human facilitators/interventionists.
2. Prior Art Statement
Businesses, corporations, governments, non-governmental agencies, non-profits and sundry organizations are hierarchical in nature and thus each has a certain culture. Stephen P. Robbins, “Management”, Third Edition, 1991, Prentice Hall, Englewood Cliffs, N.J. 07632 defines culture as a shared meaning of the values, symbols, rituals, myths and practice that have evolved over time within an organization. It is a perception of the organization not from one individual's perspective but every entity that observes the organization. To quote Robbins from page 71, “(J)ust as tribal cultures have totems and taboos that dictate how each member will act toward fellow members and outsiders, organizations have cultures that govern how members should behave. The culture conveys assumptions and norms governing values, activities and goals. In doing so, it tells employees how things should be done and what's important.” Most individuals conform generally to the organization's culture however, individuals also carry with them their own characteristics. Therefore, an individual's behavior comprises that individual's attitudes, emotions, personality, perception, learning and motivation when acting independently, however, when acting within an organization, the individual's behavior may also comprise attitudes, perceptions, teachings and motivations of the organization.
Robbins states that there are at least three different, distinct types of groups. Command groups are determined by a rigid organization chart and as such are hierarchal. Joined groups consist of members that have associated themselves with other members to advocate a common interest such as unions, to bond together for social interests, such as associations or that have a common affliction, addiction or malady and thus are seeking a treatment for that condition such as twelve step groups. Appointed groups consist of persons working together to complete a job task. Appointed groups, hereinafter, task specific teams, generally cross command relationships and often even organizations.
Though most organizations have attempted to improve decision making through the employment of task specific teams, those task specific teams carry the culture of the entity which influences the activities of the members of the team as well as the characteristics of each individual. Thus, in every team there is an organizational bias and a plurality of individual biases so it does not follow logically that a task specific team within an organization is comprised of the sum of the individuals within the team as the behavior of a group of individuals is different in the team environment than when the individuals are acting alone. Cross disciplinary teams may further carry competing cultures into the task specific team work activities as the various disciplines within an individual organization may have different cultures. Moving outwardly from individual organizations to inter disciplinary task specific teams, those members from the individual organizations who comprise a task specific team infuse into the inter disciplinary task specific team the cultures of the individual organizations further exacerbating proper decision making. Accordingly, it is understandable that task specific teams go through several stages of group development. Robbins defines these stages as forming, storming, norming, performing and adjourning. In the forming stage, individuals deal with the uncertainty of the group's purpose, structure and leadership while the storming stage surfaces the competing cultures and competing individual behaviors. Fortunately, in the norming stage, the group solidifies and assimilates a common set of expectations whereupon the group can perform in the performing stage to complete the charge given the task specific team. The adjourning stage disbands the group after task completion.
Luechtefeld, et al., in “Expert System for Team Facilitation Using Observational Learning,” 37TH ASEE/IEEE Frontiers in Education Conference, Oct. 10-13, 2007, Milwaukee, Wis., Session 1530, state that “(H)istory attests to the catastrophic consequences of team dysfunctions and neglect of group dynamics. For example, the space shuttle Challenger and Columbia tragedies can be attributed to failures in team skills. The Columbia Accident Investigation Board found that ‘the hole in the wing of the shuttle was produced not simply by debris, but by holes in organizational decision-making. Furthermore, the factors that produce the holes in organizational decision-making are not unique to today's NASA or limited to the shuttle program, but are generic vulnerabilities that have contributed to other failures and tragedies across other complex industrial settings’. Such conflicts and team dysfunctions are related to difficulties of team members sharing their perspectives and making tradeoffs. Since engineering teams are often multi-disciplinary, the complex set of problems that engineers face need to combine the expertise of different disciplines. Also, to make the project successful they need to collaborate with others in a team who may have different perspectives and technical objectives. The quality of decision-making in these contexts is enhanced by increasing openness and interdependence, and diminished when team members regulate or ignore certain information. While engineering institutions regularly give students projects involving technical knowledge, all too often students are put in project teams where they are expected to work together successfully without sufficient support in interpersonal and team skills Mere placement in teams does not guarantee the learning of these skills.”
Contrasting task specific teams from other collections of individuals, i.e., joined groups such as twelve step groups, a task specific team is generally charged with a non-programmed decision making process to benefit the organization rather than the series of programmed steps to benefit an individual. Programmed decision making processes for modification of individual behaviors is characteristic of twelve step groups and therefore the steps toward behavior modification have been well established. In non-programmed decision making, the task specific team has an identified goal so the task specific team preferably gathers information from a variety of sources, identifies a plurality of alternative actions, assesses the probability of success of each of the alternative actions, including synergistic outcomes and the value of each alternative action toward the identified goal and bases the team decision upon the alternative having the greatest value toward the identified goal. Gregory Moorhead and Ricky W. Griffin, authors of “Organizational Behavior”, 1995, Houghton Mifflin Co., 222 Berkeley Street, Boston, Mass. 02116, set forth characteristics of programmed and non-programmed decisions which lists the programmed decision characteristics as well structured, repetitive, routine with clear, specific instructions, readily available information, solutions based upon established rules with minor consequences for the organization. In contrast, non-programmed decision characteristics are poorly structured, the frequency is new and unusual, the goals are vague, the information is not available or must be developed, involve problem solving skills, judgement and where major consequences are likely for the organization. Accordingly, a great deal of uncertainty surrounds the non-programmed decision making process and the associated risks are immense. Various attempts have been made to assist individuals with improving individual skills, personal communications, personal memory aids, decision trees, feed-back loops, writing aids, personal weight loss, individual mental acuity, overcoming addictions though all these attempts are geared to individuals, whether acting alone or in as a individual in a self-help group, not teams charged with a specific vexing problem.
On the other hand, group facilitation is a process in which an entity, usually a person, acceptable to all members of the group, is substantively neutral and has no decision making authority intervenes to help a group improve the way it identifies and solves problems and makes decisions in order to increase the group's effectiveness. Preferably, the entity employs teachings from the field of organizational behavior, particularly, teachings from various studies of group dynamics or team dynamics. Interventions in team proceedings to foster decision making may employ rules based on the work of Argyris, et al., from the book entitled “Action Science: Concepts, Methods, and Skills for Research and Intervention,” Chapter 8, Jossey-Bass, San Francisco, 1985.
Artificially intelligent systems exist for entertainment and self-help. These artificial intelligent systems are virtual robots commonly known as chatterbots or chatbots. Chatbots usually interact with a single individual through an Internet portal and the chatterbot uses statements made by the individual during the communication with the chatterbot to generate additional questions or statements. Thus, it is known to provide a virtual robot that focuses on analyzing what is communicated and returning statements or questions to continue the conversation. This is akin to the “Active Listening” programs used widely by motivational and self help groups. For instance, see the “chatterbots” Eliza, Elizabeth, Gurubot and Nicole available on the Internet. However, these chatterbots generally only interact with a single individual at a time and do not embody the knowledge of an expert facilitator/interventionist. Therefore, no facilitation of the exchange of information, no method of questioning a direction for a conversation between two or more people is provided, nor is there a focus on definitive declarations, negative statements, comparative words, phrases and patterns of speech.
Expert systems are known that provide information to the patient and/or to assist medical personnel in diagnosing a medical condition. The systems are highly context specific keying on input of patient symptoms and follow a decision tree model that embodies knowledge from experts in the medical field. A typical instance is the U.S. Pat. No. 6,270,456 B1 issued on Aug. 7, 2001 to Edwin C. Iliff, though many others have been granted to Iliff and other inventors. Thus, these expert systems have an ending point at the end of one of the branches of the decision tree and return only a single output for a single user. In addition to the above limitations there is also no means to further communications between individuals or members of teams, separate teams or teams in disparate locations.
It is further known to provide changeable scripts, a back-end feedback loop, a supervisor and an editor for identifying and testing the context of an input from a user and interacting with the user. The latter two may be human, but need not be so. The scripts may be written by users, programmers or automated learning programs. There are multiple categories, scripts, user records, robot objectives and local variables. Each script contains information about a particular subject and therefore the system “knows something” about that subject. The system also maintains a list of active subjects that are the current focus of the conversation so each may be accessed throughout the conversation, however, it appears that the user must initiate any change in subject, or ask the same question multiple times to sequence through the hierarchy of subjects, as the program returns a negative response when the questioning word does not fit with the last subject discussed. For instance, see U.S. Pat. Nos. 6,314,410B1, 6,363,301B1, 6,604,090B1 issued Tackett, et al., on Nov. 6, 2001, Mar. 26, 2002 and Aug. 5, 2003 respectively and the U.S. Pat. No. 6,629,087B1 issued Sep. 30, 2003 to Benson, et al. The '301 patent contains back-end learning entered in a “Predictive Features Database” which is then used to generate Gerbil source code to respond to input questions and provide answers. The '090 patent brings in a “specificity” measure by looking for the number of unusual words used in a request. The '090 patent also brings in condition levels, matcher blocks and activator blocks to order the specificity measure according to the values assigned to the words. Finally, the '087 patent provides for creation of new topics that are then incorporated into the scripts compiled in the runtime executive processor. Though these systems are designed to generate source code, create new topics and assign a specificity value to each generated question, source code generated by this method would return only one response and thus leave out alternative responses. Furthermore, Tackett, et al., and Benson, et al., do not appear to provide for monitoring interactive communication between multiple users on the same topic, or multiple topics, as would be the case in team conversations.
It is also known to provide a system for interactive preventative medical guidance and commercial goal management comprising a polling means for creating a database of personalized input data indicative of an individual's particular behavioral issue, an evaluation means, a mediation means, a program means and a feedback means. For instance, see the U.S. Pat. No. 5,722,418 issued on 3 Mar. 1998 to L. William Bro. The evaluation means and the mediation means are conducted by a human interventionist, usually a medical professional, and the feedback means is initiated by the human interventionist. The feed-back to the patient requires the technical skills of the human interventionist in the field, thus Bro is context based and the interventionist reacts to the context of the response and provides a context based intervention relative to the malady. Accordingly, each individual's behavior in a joined group would receive substantially the same predetermined response that all others in the joined group would receive in response to specific questions. Furthermore, the system of Bro is “closed ended,” as each set of predetermined responses has an end, and action by the interventionist is required before a new set of predetermined responses can be started. Thus, Bro does not, and cannot, act autonomously, does not address a team, is skilled in the technical field of the issue and thus carries a certain bias toward that field, can only provide preprogrammed rules provided by a technical interventionist and does not act in real time therefore, even if utility for team decisions could be found in the teachings of Bro, the time required to reach consensus in a team environment would be excessive and costly. Thus, the need for an autonomous system, acting wholly independent of a human interventionist and thus avoiding the cost associated therewith, is needed to facilitate team decision making processes where characteristics are poorly structured, the problem is new and unusual, the goals are vague, the information is not available or must be developed. There is also a need for an autonomous system that is active as long as the participants are actively communicating, such as in an appointed team meeting. A further need exists for an autonomous system that does not rely upon the context of the discussion but rather upon particular words as triggers to provide instantaneous intervention to the patterns of interactions established by individuals of the group based upon teachings of organizational behavior housed in and automatically, instantaneously recoverable from a database.
Additionally, it is known to provide a system to help the user in exercising professional judgment in the course of authoring of a document by executing a question procedure that includes a reference to another procedure that takes into account an answer given by the user to another question, the procedure repeated until all questions material to the completion of the document are complete. For instance, see the U.S. Pat. No. 6,009,420 issued on Dec. 28, 1999 to Fagg, III, et al. No means to monitor conversation between members of a group is provided, nor is there any focus on particular words, phrases, definitive declarations, negative words or patterns of speech to enhance authoring of the document.
Software tools are available to assist individuals with constructing decision enabling applications using case-based reasoning. For instance, see the product ESTEEM from Esteem Software Inc., 1660 S. Amphlett Blvd., Suite 350, San Mateo, Calif. 94402. The software tool contains hybrid cases and rules, similarity assessment and learning through adaptation of prior experience, however, the software tool is limited to single individuals for single end uses and does not provide interactive intervention to multiple persons or receive input in multiple formats. Thus there is a great need for an intervention tool to help groups surface all information relevant to the subjects being discussed.
A calendar software tool is available to assist an individual to draw upon the individual's database of information regarding counterintuitive inputs to the calendar Sensi-Cal, uses ThoughtTreasure a database embracing common sense knowledge and reasoning mechanisms. SensiCal is described in the article “A Calendar with Common Sense,” by Erik T. Mueller in the Proceedings of the 2000 International Conference on Intelligent User Interfaces, pages 198-201 published in New York in Association for Computing Machinery. SensiCal interacts with a single user acting upon that user's inputs to the database returning responses based upon subsequent inputs to the calendar to remind of conflicts. The calendar cannot accommodate multiple users, does not perform in group interactions nor receive input from multiple input formats. Therefore, there is still a need for a networked complex for facilitating team proceedings comprising multiple user interfaces, multiple input and output devices, an operating system having at least one database containing a plurality of rules and an artificially intelligent system having means for monitoring patterns of interaction in an exchange of information to ferret out obstacles in proper decision making.
Also, it is known to provide a method of creating user-friendly architectural workspaces using agents that can be human, organizational, machine and/or electronic. The method is substantially “Orwellian” in nature, allowing control of agents by other agents, measuring the performance of agents, comparing the performance against an expected performance and modifying the agents based on the difference between actual and expected performance. In many places, the description includes feedback in the form of questions pertaining to the process undertaken and provides for suggesting alternative solutions or querying if an input solution fits a known model. The method is also context specific, comparing each entry with the system with the known architectural models. For instance, see the U.S. Pat. No. 6,292,830 B1 issued on Sep. 18, 2001 to Taylor, et al. Taylor, et al., does not however, monitor communications between individuals in order to make suggestions or return questions to improve the communications between the individuals. When all possible iterations have been considered, the process terminates resulting in a selection of only one developed workspace. It would appear then that multiple considerations would be denied. Limitations of the other prior art references are also applied to this patent.
Finally, it is known to provide a method of automated facilitation of group support systems to buttress facilitation efforts in managing behavior in the virtual environment. See for instance the article “Embedding Facilitation in Group Support Systems to Manage Distributed Group Behavior,” Lopez, et al., Proceedings of the 35th Hawaii International Conference on System Sciences—2002. Lopez, et al., provide for an intelligent agent to automate facilitator interactions for routine behaviors, however, when the ability of the intelligent agent is exceeded, a human facilitator is invoked. In Lopez, et al., the intelligent agent behavioral indicators act as the “eyes and ears” of the facilitator and “ThinkLets” are suggested to the facilitator, clearly indicating that the system is not continuously responding to the participants and that intervention by the facilitator is required. Thus, Lopez, et al., teach that the knowledge base is solely for the use of the facilitator, that is, a human interventionist, as the facilitator is key to the workings of that system. Accordingly, Lopez, et al., have an end point beyond which the intelligent agent lacks ability to intervene thus driving up costs for teamwork decision making. Additionally, the interventionist of Lopez, et al., could be the team leader, another team member or a member of management which would introduce organizational bias into the team proceedings. The sum of the references indicates a need for an autonomous system, acting wholly independent of a human interventionist, to facilitate team decision making processes where characteristics are poorly structured, the problem is new and unusual, the goals are vague, the information is not available or must be developed. There is also a need for an autonomous system that is active as long as the participants are actively communicating, such as in an appointed team meeting yet benefiting from an automatic intelligent agent, thus avoiding the cost associated with an human interventionist. A further need exists for an autonomous system that does not rely upon the context of the discussion but rather provides instantaneous intervention to the patterns of interactions established by the individuals of the group based upon teachings of organizational behavior housed in and automatically, instantaneously recoverable from a database.